AI as an API - Part 2 - Deploy an ML Model Rest API using Encryption, Docker, Keras, FastAPI & NoSQL

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AI as an API - Part 2 - Deploy an ML Model Rest API using Encryption, Docker, Keras, FastAPI & NoSQL PART 1: https://www.youtube.com/watch?v=56qQNcHJxyQ Web Scraping with Python on a Schedule: https://www.youtube.com/watch?v=NyDT3KkscSk Learn to create & deploy a deep learning algorithm into a production REST API using Python, Keras, FastAPI, & NoSQL. ⦿ Build a Spam Classifier with Keras (post): https://kirr.co/u2tpsc ⦿ UCI Datasets: https://archive.ics.uci.edu/ml/datasets.php ⦿ Project Tutorials: https://cfe.sh/projects ⦿ Sign up for DataStax AstraDB: https://dtsx.io/3lC4cWy ⦿ Reference Code: https://github.com/codingforentrepreneurs/AI-as-an-API-Course-Reference ⦿ Production Code: https://github.com/codingforentrepreneurs/AI-as-an-API ⦿ Subscribe: https://cfe.sh/youtube 00:00:00 Welcome to Part 2 00:00:22 Pick a Cloud Provider 00:02:32 Generate SSH Keys 00:06:10 Add SSH Key to Linode 00:07:51 Provision VM on Linode 00:13:22 SSH into VM 00:16:12 Install GIT & Python Pip 00:19:23 Clone Public Project 00:22:50 Clone Private Repo 00:28:42 Install Docker 00:33:29 Why We Use Docker 00:37:44 Add Dockerfile 00:46:16 Build Docker Project & Enter Docker Bash 00:53:03 Environment Variables & Entrypoint 01:02:59 Added Pypyr Pipelines 01:08:20 Securing a Directory with Cryptography 01:20:47 Resuable Encryption Module 01:29:39 Pipelines for Encryption & Decryption 01:36:08 Production Environment Updates 01:41:50 Final Considerations for Updating our Systems 01:50:44 Thank You and Next Steps